Traffic congestion is a challenge that affects several levels of modern society throughout the world. Building reliable and cost-effective traffic monitoring systems can be an important aspect in addressing this phenomenon. Historically, the estimation of traffic congestion has been limited to highways, and has relied mostly on a static, dedicated sensing infrastructure such as loop detectors or cameras. Estimation of traffic on the secondary road networks has not been sufficiently address, perhaps at least in part due to the cost of deploying wide networks of sensors.
Various methodologies have been proposed to monitor traffic. For example, Virtual trip lines (VTLs) have been used to sample data. VTLs are imaginary checkpoints where vehicles emit a timestamp when they pass by. Some have proposed to derive signal timing from discontinuities in the velocities of floating vehicle data, which suffer from high noise levels. Recently, it has been postulated that GPS devices in cellular phones and in commercial fleets could be utilized to match the map location and trajectories of the devices using a path interference filter. Previous attempts to estimate traffic suffer from various limitations that are addressed herein.